| Literature DB >> 31188022 |
Isabella Apruzzese1, Eunyeong Song2, Ernest Bonah3, Vernadette S Sanidad4, Pimlapas Leekitcharoenphon5, Julius John Medardus6, Nagmeldin Abdalla7, Hedayat Hosseini8, Masami Takeuchi9.
Abstract
Whole-genome sequencing (WGS) has become a significant tool in investigating foodborne disease outbreaks and some countries have incorporated WGS into national food control systems. However, WGS poses technical challenges that deter developing countries from incorporating it into their food safety management system. A rapid scoping review was conducted, followed by a focus group session, to understand the current situation regarding the use of WGS for foodborne disease surveillance and food monitoring at the global level and identify key limiting factors for developing countries in adopting WGS for their food control systems. The results showed that some developed nations routinely use WGS in their food surveillance systems resulting in more precise understanding of the causes of outbreaks. In developing nations, knowledge of WGS exists in the academic/research sectors; however, there is limited understanding at the government level regarding the usefulness of WGS for food safety regulatory activities. Thus, incorporation of WGS is extremely limited in most developing nations. While some countries lack the capacity to collect and analyze the data generated from WGS, the most significant technical gap in most developing countries is in data interpretation using bioinformatics. The gaps in knowledge and capacities between developed and developing nations regarding use of WGS likely introduce an inequality in international food trade, and thus, relevant international organizations, as well as the countries that are already proficient in the use of WGS, have significant roles in assisting developing nations to be able to fully benefit from the technology and its applications in food safety management.Entities:
Keywords: Food and Agriculture Organization of the United Nations; developing countries; food safety; foodborne disease surveillance; next-generation sequencing; whole-genome sequencing
Mesh:
Year: 2019 PMID: 31188022 PMCID: PMC6653794 DOI: 10.1089/fpd.2018.2599
Source DB: PubMed Journal: Foodborne Pathog Dis ISSN: 1535-3141 Impact factor: 3.171
Scoping Review Keywords and Numbers of Relevant Hits
| 1 | WGS | Outbreak | 671 | 292 | |
| Investigation | 546 | 105 | |||
| Identification | 486 | 59 | |||
| Detection | 468 | 59 | |||
| Incident | 678 | 5 | |||
| Investigation | 544 | ||||
| Identification | 272 | 2 | |||
| Detection | 287 | ||||
| Case | 11,530 | 202 | |||
| Investigation | 8673 | 38 | |||
| Identification | 3639 | 34 | |||
| Detection | 3275 | 29 | |||
| NGS | Outbreak | 833 | 89 | ||
| Investigation | 633 | 19 | |||
| Identification | 567 | 26 | |||
| Detection | 614 | 25 | |||
| Incident | 830 | 7 | |||
| Investigation | 590 | 1 | |||
| Identification | 357 | ||||
| Detection | 406 | 1 | |||
| Case | 17,554 | 815 | |||
| Investigation | 11,478 | 37 | |||
| Identification | 7455 | 145 | |||
| Detection | 7777 | 146 | |||
| 2 | Developing countries[ | Microbial safety | 21,019 | 97 | |
| NGS | 225 | ||||
| WGS | 174 | ||||
| Outbreak | 60,840 | 2627 | |||
| NGS | 331 | 1 | |||
| WGS | 375 | 1 | |||
| Food safety | 99,188 | 1040 | |||
| NGS | 433 | 1 | |||
| WGS | 342 | 1 | |||
| 3 | WGS | Data share | 2990 | 10 | |
| Trace | 741 | ||||
| Routine surveillance | 250 | ||||
| Transmission | 761 | 1 | |||
| NGS | Data share | 5608 | 27 | ||
| Trace | 1080 | ||||
| Routine surveillance | 95 | ||||
| Transmission | 1194 | 3 | |||
| Genotyping | Data share | 72,162 | 132 | ||
| Trace | 10,255 | 1 | |||
| Routine surveillance | 3670 | 1 | |||
| Transmission | 19,277 | 19 | |||
| 4 | Developing country | WGS | 2337 | 8 | |
| Source attribution | 89 | ||||
| Interpretation | 850 | 1 | |||
| NGS | 2582 | 25 | |||
| Source attribution | 66 | ||||
| Interpretation | 917 | 3 | |||
| 5 | Trade | WGS | 1356 | 4 | |
| Trace | 350 | ||||
| Reference | 962 | 1 | |||
| Frontline tool | 4 | 0 | |||
| Phylogenetic | 88 | 0 | |||
| NGS | 1277 | 27 | |||
| Trace | 289 | ||||
| Reference | 888 | 1 | |||
| Frontline tool | 12 | 0 | |||
| Phylogenetic | 184 | 1 | |||
| 6 | WGS | Prediction | 3215 | 79 | |
| Management | 1128 | 6 | |||
| Risk assessment | 621 | 1 | |||
| Forecast | 609 | 1 | |||
| Management | 366 | 0 | |||
| Risk assessment | 197 | 0 | |||
| 7 | WGS | Developing country | 2337 | 8 | |
| Retrospective investigation | 170 | 0 | |||
| Microbiology investigation | 305 | 0 | |||
| Epidemiology investigation | 287 | 0 |
A rapid scoping review was conducted to outline the key thematic areas on the topic of WGS applications in food safety management. As the relevance was verified in the process, the higher number of hits indicates that the topic has been widely discussed in published literature and the lower number of hits indicates that the supporting evidence to the topic is not sufficiently available in published literature.
ScienceDirect. Available at: https://www.sciencedirect.com
PubMed—NCBI. Available at: https://www.ncbi.nlm.nih.gov/pubmed
Based on the UN country classification and terminology. Available at: https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/WESP2018_Full_Web-1.pdf
NGS, next-generation sequencing; WGS, whole-genome sequencing.
Summary of the Focus Group Results
| 1 | Use of WGS for official food safety management activities | • WGS is not being used for food safety management in any countries that participants are from.[ |
| 2 | WGS data collection and accessibility to the global database | • No national database of WGS for food safety exists in any countries participants are from. |
| 3 | WGS data generation | • Three participants are involved in WGS data generation and the data are shared on some global databases. |
| 4 | Food safety data sharing | • Some countries share food safety-related data for research purposes. |
| 5 | Basic laboratory capacity | • Participants confirmed that their countries have reference laboratories that can isolate pathogens, thus basic microbiological capacity exists. |
| 6 | Food and environmental monitoring for foodborne pathogens | • All participants confirmed that clinical samples are often checked on a regular basis, but food and environmental monitoring for foodborne pathogens is usually done on an |
| 7 | Technical challenges to improve food monitoring systems | • As food safety is a cross-cutting issue, communication and collaboration with different sectors (agriculture, health, trade and commerce) are a challenge. |
| 8 | Bioinformatic capacity | • Capacities exist at the research level, but all participants confirmed that the capacity is not sufficient at the government level. |
| 9 | Needs in improving WGS knowledge and capacity | • There is a strong need in raising the awareness of the potential of WGS for food safety in developing countries. |
| 10 | Potential of WGS in developing countries | • Participants strongly agreed that WGS would increase the number of detected food safety incidences and outbreaks. |
A focus group session was conducted with technical experts (n = 6) from developing countries to assess the current situation regarding WGS applications in food safety management for developing countries. Based on a standard pattern of analyzing a focus group study, the items in the left column represent thematic ideas and the items in the right column represent the indexed and mapped interpretations of quotes.
Ghana, Iran, the Philippines, Sudan, Tanzania, and Thailand.
AMR, antimicrobial resistance; INFOSAN, International Food Safety Authorities Network; WGS, whole-genome sequencing.